Data-driven Modeling Prescriptive Analytics Risk 
Rocket-Powered Data Science
JULY 19, 2023
I recently saw an informal online survey that asked users which types of data (tabular, text, images, or “other”) are being used in their organization’s analytics applications. The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data.
Cloudera
MARCH 2, 2018
If you do an internet search for ‘data-driven disruption’ you can find articles about almost every industry being disrupted by digitalisation and new applications of data. While there are instances of data-driven efforts in the nonprofit sector, they are not as widespread as they can be.
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Cloudera
AUGUST 25, 2020
Thank you for joining us for part two of our discussion around data, analytics and machine learning within the Financial Service Sector Dr. Harmon. One of the key takeaways from recent times that should be considered into the future, is that banks need to rethink how they look at tail risk or extreme events that rarely happen. .
IBM Big Data Hub
JULY 6, 2023
While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? One challenge in applying data science is to identify pertinent business issues.
DataRobot Blog
MARCH 15, 2022
The main themes emerging from our conversations cover data integration, security and humility, strategy, and workforce development: Join siloed data together to create longitudinal, ready-to-analyze datasets. Secure data sharing and AI humility is a necessity.
FineReport
MARCH 24, 2024
Rapid technological advancements and extensive networking have propelled the evolution of data analytics, fundamentally reshaping decision-making practices across various sectors. In this landscape, data analysts assume a pivotal role, tasked with interpreting data to drive informed decision-making.
Cloudera
JULY 18, 2018
As such, we are witnessing a revolution in the healthcare industry, in which there is now an opportunity to employ a new model of improved, personalized, evidence and data-driven clinical care. Additionally, organizations are increasingly restrained due to budgetary constraints and having limited data sciences resources.
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